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Talk given at The Contours of Algorithmic Life, a conference at UC Davis -- May 15-16, 2014.

Here's the abstract:

Traditionally, computer scientists define an algorithm as a list of instructions for accomplishing a single goal. This definition treats an algorithm as (1) a coherent, usually textual, single object that (2) can be separated from its technological execution. Instead, we argue for the usefulness of studying algorithms in and as action. Algorithms-in-action, particularly computational algorithms, depend on actors outside them: the sources of the data they require as inputs, the machines that execute them, the storehouses that maintain their results and make them available for other processes, and so on. Algorithms are not stable texts but rather more-or-less stable agglomerations of people, machines, policies, data, and so on whose dimensions and components change over time. Our talk will examine the multiplicity and contingency of algorithms through two case studies from very different algorithmic sites -- architectural software, and online dating services. Using those sites as springboards, it will argue that taking algorithms as multiple rather than singular and as material agglomerations rather than discursive texts opens up new entry points for creative and critical practice in design, the arts, and engineering.

Hi there – in this talk, we’ll be looking at potential tactics for using algorithms in creative practice.

What is the “algorithm” at stake in our discussion? We’ll start with one specific, influential definition. We return to one central to the discipline of computer science, whichcomes from a classic textbook by Donald Knuth, the founder of the field of algorithm analysis(1) SET OF RULES: algorithms are not the operations themselves; they are abstracted from implementation. The algorithm is a set of rules which is different from the computer code that implements those rules. (2) PROBLEM-DEFINED: algorithms are teleological; they are constructed around the successful resolution of a single goal or “type of problem.”---------------And this notion is picked up in writing on it:TedStriphas: “sets of procedures that specify how someone or something ought to proceed given a particular set of circumstances.” http://www.thelateageofprint.org/2012/11/28/algorithms-are-decision-systems/

Online dating is an interesting case study because it’s a service in which people grant algorithms – matchmaking algorithms – power over a hugely consequential part of their lives. The genesis of this work is a study I did with Yahoo! Research in 2007, but its points are still relevant.This is the story we usually get about how online dating works. Daters make profiles, which combine self-description in images, free-entry text, images, and structured data (such as ages and weights) and their own expectations for a desirable match. They can also send various messages to other daters on the site. Then the algorithm matches expectations to profiles and outputs a list of results. And from that, love!It’s the story implicit in the images and copy in Eharmony’s current home page, up top.

But after talking with developers, designers, online daters, there are actually quite a few more actors playing a role in this story – and they act quite differently depending on where and how one enters it, and what kind of control one has over it. It becomes a messy web of interactions among actors, some of whom do not know the others exist. Thepseudocode, or rule set– what’s within that yellow box – is only one small part.

I’m going to fall back on the algorithm’s human interlocutors to give us some sense of where and how the matching algorithm might be operating here. For the developers of the system: the algorithm is not a mystery – instead, it’s the actions of human men and women, usually conceptualized along gender binaries .The goal: How canalgorithm(s) mediate their (conflicting) desires?For daters with interests and tastes (such as latex fetishes and BDSM, in the case of this quote) that the business rejects, “the algorithm” as implemented by a corporation, is as much enemy as partner – it demands that they obscure a hugely important part of their sexual/romantic behavior. So one algorithm – the content filtering one – must be tricked, while in order to properly do its job the matching algorithm must be augmented by knowledgeable humans.For other daters, the algorithm/site is a kind of personified, omniscient figure who “knows” them better than they know themselves. In this case, the woman in question is telling a story of an initial rejection. But when faced with a “perfect match,” at least in this story, the rejector decided to give it a try. Which is kind of strange – in this case, the algorithm has “failed” by Knuth’s terms --- But that seeming failure is turned to success by the woman’s belief that the algorithm musthave succeeded.

Discursive components, then, are part of what defines the problem or goal for the algorithm to solve or accomplish, and helps the algorithm do so. But if that problem/goal, if we take Knuth seriously, is what defines the algorithm, then we have a bit of a problem: more than one type of problem means more than one algorithm.

So perhaps we should think of any algorithm as, in practice, multiple rather than singular.We’re drawing here on the work of Annemarie Mol in studying the disease.As Mol writes, a disease – or an algorithm -- comes into being – and disappears – with the practices in which it/they are manipulated. (In this case, software development, BDSM, and online dating in general). There is not a unified disease being *seen* differently by different people. The disease is multiple in itself.

In practice, the matching algorithm is multiple – in the personified, omniscient site which induces people to go on dates they wouldn’t normally try; in the service which needs to be fooled for the users’ own good, in the tweakable tool for navigating (making?) gender difference. “The algorithm” acts differently in the world depending on how one encounters it. Here’s my somewhat impressionistic sketch trying to get that idea across. It’s a cluster of entities blinking on and off, whose boundaries are more or less permeable and whose “thereness” is more or less active. As a heterogeneous entity, “the algorithm” holds together multiple instantiationsin conversation under a single name. That’s how an online dating website can work for the diverse interests who participate in it.So one way is to think of this diagramas trying to illustrate the relationship between “algorithmic life” and a set of procedures being enacted in practice. Let’s look at another example, this time emphasizing the role of the materials of enactment.

Fabrication machines, sometimes called CNC or computer-numeric controlled machines -- take instructions from a computer to move That language of control is called G-codeFabrication doesn’t look much like online dating, but there are some unexpected similarities. Which shows us how material enactments make a multiplicity out of a single algorithm.An architecture class taught by Jason Kelly Johnson and Michael Shiloh at CCA. In particular, they’re both creative practice. Daters craft profiles iteratively, working with the algorithm in conversation to figure out how to show themselves to the algorithm in order to best find and be found. Here, the creative practice is more obvious: the students in Johnson and Shiloh’s class are using machines to turn the pure geometry of drawing algorithms into 3D form. Or are they?

Let’s investigate it the same way.Modelling software turns pseudocode into implementable code, which is then piped to the board running the fabrication machine, which deposits clay on the bed to form the object…which slumps and warps in the interaction among the wet clay, gravity, and the drying air.

But as Johnson tells it, there a was a split in the notion of what – or who – is doing the creativity in the machine. Is it the students or the inter-acting elements?

We can pull out two different discourses of the algorithm which suggest different “success states” for it.To the students (at least from Johnson’s narrative), the machine is a stable mediator of the algorithm: it is supposed to print perfectly. So the algorithm is “done” when the printing stops. For Johnson, the machine and environmental forces such as gravity, air temperature, and so on are productive part of the algorithm as a system – the algorithm is “done” when the glitches that occur in the interaction between wet clay, irregular servo motors, and gravity spurs reconsideration of architectural form.

The algorithm is multiple because it is inescapably material in being enacted. So the question is, what tactics provide us with points of leverage -- where we can intervene and create opportunities to act multiply and differently?

As designers, we’re interested in the notion of intentionally intervening in the world. In a traditional notion of an algorithm, we enact change by changing the written instruction. Action extends from the locus of the machine text. Foregrounding practice and looking at an algorithm as a thing that is enacted a variety of different but interconnected ways grants designers new entry points and new ways to manipulate and explore these systems.

I’m currently developing a project entitled “Being the Machine” that looks towards rearranging components in the practice of using digital fabricators in order to provoke a specific kind of discourse. Rather starting from the technological idea of “what new” technology to design, my unit of design has been a certain kind of discourse about fabrication: a discourse that questions relationship between human and machine and the tensions between new and old forms of “making.” Which leads to the question: how do you “write” an algorithm in action and how do you do so in such a way to provoke a particular story?

Design does not exist in a vacuum, and when we are designing, we are both consciously and unconsciously drawing relationships from different objects, experiences, assumptions, and practices. When the algorithm is located exclusively in technological objects, objects take precedence in dictating how a design might function. Yet, this implies that actions can be reduced to certain parts and that objects are more or less interchangeable. For instance, if someone wants to design an app that attempts to recreate the aura of a hand-written letter, they might suggesting mimicking existing letter by writing with a pen on a tablet will achieve the same effect. By foregrounding practice, Mol’s concept of the multiple emphasizes the relationship between objects in a socio-technical system. Drawing design inspiration then comes from relating discourses to practices (objects in action) rather than discourses to objects alone. In order to inform the design of a discourse that critically questions relationships between humans and mechanical technologies, I look to art practice which has a long history of such discourse.

Foregrounding practice allows us to look How do you figure out which set will provoke discourse? Look outside of disciplinary boundaries – I have found the history of performance art to be particularly exemplary as a way that people have come to question and epxlore the relationships between body and machine, control and automation. Here we are seeing two instances in which performance has been evoked to explore the idea of the machine and production

What this idea and discourse around performance has led me to is a fabrication machine that is essentially a rule following human. (Explain the concept). The user is defined by the designer (me) and told to embark on a public performance of making. Instead of focusing on the “new technology” I make an augment that recombination of existing technologies fundamentally change fabrication in action and that it can be limiting to think of innovation as something that is rooted in new technologies. Automated actions like futurists and Bauhaus, chance and indeterminacy in the materials that are used. ..but I imagine an argument where someone might say, “why call this an algorithm?”

As Knuth wrote himself, the best way to learn what an algorithm is all about is to try it.Thanks!